Application of F-Continuous Distribution in Predicting Extreme Environmental and Engineering Events

The F-continuous distribution, a flexible model for handling various data distributions, is increasingly used in fields such as environmental science, material science, and engineering for predicting extreme events. This proposal aims to explore the use of the F-continuous distribution to model and predict extreme environmental and engineering phenomena, such as extreme temperature events, material stress failures, and other rare events. The F-continuous distribution is particularly suitable for cases where the data shows heavy tails and is capable of capturing both the central and extreme behaviors of the dataset effectively.\r\nWe focus on two case studies to demonstrate the application of the F-continuous distribution: (1) predicting extreme temperature events like heatwaves and cold snaps based on historical temperature data, and (2) assessing material stress testing data to predict the likelihood of failure under extreme conditions. For both cases, we apply statistical methods, including parameter estimation and goodness-of-fit tests, to fit the F-continuous distribution to the data and derive predictions for the return periods and exceedance probabilities of extreme events.\r\nThe results will offer valuable insights into the frequency and severity of rare events, which can help improve risk management strategies and decision-making in environmental policy and material engineering. The analysis will provide an innovative approach to predicting extreme events, enhancing the understanding of their underlying distribution patterns.